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Skip-SCSE Multi-scale Attention and Co-learning Method for Oropharyngeal Tumor Segmentation on Multi-modal PET-CT Images.

A. Biase, W. Tang, N. Sourlos, B. Ma, J. Guo, N. Sijtsema, and P. van Ooijen. HECKTOR@MICCAI, volume 13209 of Lecture Notes in Computer Science, page 109-120. Springer, (2021)

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Priyanka Nannapaneni

Nanna Bleek

Nanna Gertz

Nanna Rapp

Other publications of authors with the same name

Swin UNETR for Tumor and Lymph Node Segmentation Using 3D PET/CT Imaging: A Transfer Learning Approach.H. Chu, L. la O. Arévalo, W. Tang, B. Ma, Y. Li, A. Biase, S. Both, J. Langendijk, P. van Ooijen, N. Sijtsema and 1 other author(s). HECKTOR@MICCAI, volume 13626 of Lecture Notes in Computer Science, page 114-120. Springer, (2022)A Comparative Study of Federated Learning Models for COVID-19 Detection.E. Darzidehkalani, N. Sijtsema, and P. van Ooijen. CoRR, (2023)Deep Learning and Radiomics Based PET/CT Image Feature Extraction from Auto Segmented Tumor Volumes for Recurrence-Free Survival Prediction in Oropharyngeal Cancer Patients.B. Ma, Y. Li, H. Chu, W. Tang, L. la O. Arévalo, J. Guo, P. van Ooijen, S. Both, J. Langendijk, L. van Dijk and 1 other author(s). HECKTOR@MICCAI, volume 13626 of Lecture Notes in Computer Science, page 240-254. Springer, (2022)Slice-by-slice deep learning aided oropharyngeal cancer segmentation with adaptive thresholding for spatial uncertainty on FDG PET and CT images.A. Biase, N. Sijtsema, L. van Dijk, J. Langendijk, and P. van Ooijen. CoRR, (2022)TransRP: Transformer-based PET/CT feature extraction incorporating clinical data for recurrence-free survival prediction in oropharyngeal cancer.B. Ma, J. Guo, L. van Dijk, P. van Ooijen, S. Both, and N. Sijtsema. MIDL, volume 227 of Proceedings of Machine Learning Research, page 1640-1654. PMLR, (2023)Tackling Heterogeneity in Medical Federated learning via Vision Transformers.E. Darzi, Y. Shen, N. Sijtsema, and P. van Ooijen. CoRR, (2023)Fed-Safe: Securing Federated Learning in Healthcare Against Adversarial Attacks.E. Darzi, N. Sijtsema, and P. van Ooijen. CoRR, (2023)Exploring adversarial attacks in federated learning for medical imaging.E. Darzi, F. Dubost, N. Sijtsema, and P. van Ooijen. CoRR, (2023)Self-supervised Multi-modality Image Feature Extraction for the Progression Free Survival Prediction in Head and Neck Cancer.B. Ma, J. Guo, A. Biase, N. Sourlos, W. Tang, P. van Ooijen, S. Both, and N. Sijtsema. HECKTOR@MICCAI, volume 13209 of Lecture Notes in Computer Science, page 308-317. Springer, (2021)The Hidden Adversarial Vulnerabilities of Medical Federated Learning.E. Darzi, F. Dubost, N. Sijtsema, and P. van Ooijen. CoRR, (2023)

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Disambiguation of "Sijtsema, Nanna Maria"

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Skip-SCSE Multi-scale Attention and Co-learning Method for Oropharyngeal Tumor Segmentation on Multi-modal PET-CT Images.

Please choose a person to relate this publication to

Priyanka Nannapaneni

Priyanka Nannapaneni

Nanna Bleek

Nanna Gertz

Nanna Rapp

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Sijtsema, Nanna Maria"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Skip-SCSE Multi-scale Attention and Co-learning Method for Oropharyngeal Tumor Segmentation on Multi-modal PET-CT Images.

Please choose a person to relate this publication to

Priyanka Nannapaneni

Priyanka Nannapaneni

Nanna Bleek

Nanna Gertz

Nanna Rapp

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
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history of this post
URL
DOI
BibTeX
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APA
Chicago
DIN 1505
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Skip-SCSE Multi-scale Attention and Co-learning Method for Oropharyngeal Tumor Segmentation on Multi-modal PET-CT Images.